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cs.CL2026

FinChain: A Symbolic Benchmark for Verifiable Chain-of-Thought Financial Reasoning

Zhuohan Xie, Daniil Orel, Rushil Thareja +22

Multi-step symbolic reasoning is essential for robust financial analysis; yet, current benchmarks largely overlook this capability. Existing datasets such as FinQA and ConvFinQA em…

cs.CL2026

Is Human-Like Text Liked by Humans? Multilingual Human Detection and Preference Against AI

Yuxia Wang, Rui Xing, Jonibek Mansurov +23

Prior studies have shown that distinguishing text generated by Large Language Models (LLMs) from human-written one is highly challenging for humans, and often no better than random…

cs.CL2025

Between Underthinking and Overthinking: An Empirical Study of Reasoning Length and correctness in LLMs

Jinyan Su, Jennifer Healey, Preslav Nakov +1

Large language models (LLMs) are increasingly optimized for long reasoning, under the assumption that more reasoning leads to better performance. However, emerging evidence suggest…

cs.CL2025

GenAI Content Detection Task 1: English and Multilingual Machine-Generated Text Detection: AI vs. Human

Yuxia Wang, Artem Shelmanov, Jonibek Mansurov +23

We present the GenAI Content Detection Task~1 -- a shared task on binary machine generated text detection, conducted as a part of the GenAI workshop at COLING 2025. The task consis…

cs.CL2024

M4GT-Bench: Evaluation Benchmark for Black-Box Machine-Generated Text Detection

Yuxia Wang, Jonibek Mansurov, Petar Ivanov +11

The advent of Large Language Models (LLMs) has brought an unprecedented surge in machine-generated text (MGT) across diverse channels. This raises legitimate concerns about its pot…

cs.CL2024

SemEval-2024 Task 8: Multidomain, Multimodel and Multilingual Machine-Generated Text Detection

Yuxia Wang, Jonibek Mansurov, Petar Ivanov +12

We present the results and the main findings of SemEval-2024 Task 8: Multigenerator, Multidomain, and Multilingual Machine-Generated Text Detection. The task featured three subtask…